Computer vision is a field for processing high-dimensional data from the real world in order to produce numerical or symbolic information. A theme in the development of this field has been to duplicate the abilities of human vision by understanding images. This image understanding can be seen as the disentangling of symbolic information from image data using models constructed with the aid of geometry, physics, statistics, and learning theory. Applications range from tasks such as industrial machine vision systems to research into artificial intelligence and computers or robots that can comprehend the world around them. Computer vision covers the core technology of automated image analysis which is used in many fields. The image data can take many forms, such as video sequences, views from multiple cameras, or multi-dimensional data from a medical scanner. The track is intended to offer a forum for people interested in modeling and simulation of methods of computer vision and applications. In particular, the subjects include but are not limited to:

• Data structures and representations

• Modeling of objects or environments, including medical image analysis

• Shape and motion

• Vision systems

• Vision based navigation

• Event detection

• Vision based Interaction

• Automatic inspection

• Scene reconstruction

• Object recognition

• Learning from vision

• Related applications